What you'll be able to do- ✓Group loyalty members by recency, frequency and spend, and spot the group a recency screen mislabels in a festival business
- ✓Audit an AI persona detail by detail against what the data holds, and tell a chance regional skew from a finding
- ✓Separate a campaign's effect from the festival and from the outlets' head start, and turn the lift into margin and a decision
- ✓Test a churn score for fields known only after the event, beat a simple score, and attach an action and an opt-in check to every group
- ✓Label a sample of reviews yourself, measure how far to trust an AI's labels, and write a one-page decision memo with a claim ledger behind it
Turn loyalty, outlet-sales and review files and a question from the marketing head into a one-page decision memo you can defend — customer groups you checked against the calendar, a campaign effect with its range and its break-even, a watch-list tested for leakage, and a reading of what customers said.
⌁ How marketing analysts use AI assistants on customer, campaign, churn and review work — check the calendar before calling anyone lapsed, compare change against change, ask when each field is known, label a sample by hand, keep a ledger of where every figure came from, and report ranges and decisions to the marketing head.